Revix AI scans your repo, generates its own pattern and architecture rules, and reviews every pull request against them. It keeps learning as the repo changes. Each comment names its rule and is labeled by intent and severity. Free for public repos.
Hey Product Hunt 👋 I'm Uri. Oscar and I are building Revix AI from Barcelona.
Why we built it: LLMs made us write code much faster, but we watched quality drop and incidents go up. Review is where that should get caught, and it usually doesn't, because most review comments don't know how your repo actually does things. So people stop reading them.
Revix starts by scanning your repo and generating its own pattern and architecture rules. You don't write a rulebook. It reviews every pull request against those rules and keeps learning as the repo changes.
Each comment names the rule behind it and is labeled by intent and severity, so you know why it's there and what to fix first. The number we care about is how many comments you act on, not how many we leave.
It works with GitHub, GitLab and Bitbucket Cloud. It's free for public repos, with a 14 day trial and no card for private ones.
It's early and some comments will miss. Please be blunt: run it on a repo you know well and tell us which comment was useless and why. Oscar and I are here all day.
About Revix AI on Product Hunt
“AI code review that learns your repo's own rules”
Revix AI launched on Product Hunt on October 27th, 2026 and earned 110 upvotes and 10 comments, placing #13 on the daily leaderboard. Revix AI scans your repo, generates its own pattern and architecture rules, and reviews every pull request against them. It keeps learning as the repo changes. Each comment names its rule and is labeled by intent and severity. Free for public repos.
On the analytics side, Revix AI competes within Software Engineering, Developer Tools and Artificial Intelligence — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Revix AI performed against the three products that launched closest to it on the same day.
Who hunted Revix AI?
Revix AI was hunted by Oriol Viladrosa. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Revix AI including community comment highlights and product details, visit the product overview.
Oriol Viladrosa
Hey Product Hunt 👋
I'm Uri. Oscar and I are building Revix AI from Barcelona.
Why we built it: LLMs made us write code much faster, but we watched quality drop and incidents go up. Review is where that should get caught, and it usually doesn't, because most review comments don't know how your repo actually does things. So people stop reading them.
Revix starts by scanning your repo and generating its own pattern and architecture rules. You don't write a rulebook. It reviews every pull request against those rules and keeps learning as the repo changes.
Each comment names the rule behind it and is labeled by intent and severity, so you know why it's there and what to fix first. The number we care about is how many comments you act on, not how many we leave.
It works with GitHub, GitLab and Bitbucket Cloud. It's free for public repos, with a 14 day trial and no card for private ones.
It's early and some comments will miss. Please be blunt: run it on a repo you know well and tell us which comment was useless and why. Oscar and I are here all day.